AI-Gauge VS Code Extension

Analyzes LLM API calls in your code and suggests cheaper model alternatives.

🚀 Quick Start (2 Minutes)

1. Install from VS Code Marketplace

Ctrl+Shift+X → Search "AI-Gauge" → Install → Reload VS Code

2. That's it! ✨

AI-Gauge automatically:

• ✅ Installs Ollama (if missing)
• ✅ Downloads the AI-Gauge analysis model
• ✅ Configures everything automatically

3. Start Coding

Get instant cost optimization hints as you write LLM API calls!

🎯 What It Does

AI-Gauge analyzes your code and provides real-time feedback on LLM model usage:

# Your code:
response = client.chat.completions.create(
    model="gpt-4",  # ⚠️ Overkill for simple tasks!
    messages=[...]
)

# AI-Gauge shows:
# 💡 Switch to GPT-3.5-turbo → Save 90% ($4.50 → $0.45 per 1K calls)

✨ Features

🔍 Smart Detection

• Auto-Detection: Finds OpenAI, Anthropic, Google, and custom API calls
• Real-Time Analysis: Analyzes as you type (optional)
• Multi-Language: Python, JavaScript, TypeScript support

💰 Cost Optimization

• Savings Alerts: Shows potential cost reductions
• Model Recommendations: Suggests appropriate alternatives
• Usage Tracking: Monitors your API spending patterns

🌱 Environmental Impact

• Carbon Tracking: Estimates CO₂ footprint per API call
• Green Suggestions: Recommends efficient models
• Sustainability Focus: Helps reduce AI's environmental impact

🎨 User Experience

• Inline Hints: Cost and latency indicators in your code
• Quick Fixes: One-click model replacement
• Hover Details: Detailed analysis on demand

🛠️ Commands

• AI-Gauge: Analyze Current File - Analyze the active file
• AI-Gauge: Analyze Workspace - Analyze all supported files
• AI-Gauge: Toggle Real-Time Analysis - Enable/disable live analysis

⚙️ Settings

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                    VS Code Extension                         │
├─────────────────────────────────────────────────────────────┤
│  extension.ts          - Main entry, registers providers     │
│  llmCallDetector.ts    - Detects LLM calls via regex/AST     │
│  aiGaugeClient.ts      - Calls local Ollama inference        │
│  diagnosticsProvider.ts - Shows warnings + quick fixes       │
│  inlineHintsProvider.ts - Shows inline cost/latency hints    │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│              Local Ollama Inference                         │
│                  Fine-tuned Phi-3.5 Model                   │
│                                                              │
│  Model: ajayvenki01/ai-gauge                                 │
│  Runs: Locally on user machine                               │
│  Privacy: 100% local processing                              │
└─────────────────────────────────────────────────────────────┘

🔍 Detection Patterns

The extension detects LLM calls using intelligent patterns:

OpenAI (Python)

client.chat.completions.create(model="gpt-4o", ...)
client.beta.chat.completions.parse(model="gpt-4o-mini", ...)

Anthropic (Python)

client.messages.create(model="claude-3-opus", ...)

Google (Python)

model = genai.GenerativeModel("gemini-pro")

OpenAI (JavaScript/TypeScript)

const completion = await openai.chat.completions.create({
  model: "gpt-4",
  messages: [...]
});

💡 User Experience Examples

Inline Hints (always visible):

response = client.chat.completions.create(...)  # ⚠️ $5.00/1k • slow → 💡 save 90%

Diagnostics (squiggly underline):

• Yellow information squiggle on overkill model usage
• Hover for detailed analysis with reasoning

Quick Fix (lightbulb):

• Click the lightbulb to replace model with recommended alternative
• Automatic code transformation

🔧 Manual Setup (Advanced Users Only)

If auto-setup fails, you can manually configure:

1. Install Ollama

curl -fsSL https://ollama.ai/install.sh | sh

2. Pull AI-Gauge Model

ollama pull ajayvenki01/ai-gauge

3. Verify Installation

ollama list  # Should show ai-gauge model

🛠️ Development

For extension developers:

Prerequisites

• Node.js 16+
• VS Code 1.74+

Setup

cd ide_plugin
npm install
npm run compile

Development Commands

npm run watch      # Watch mode compilation
npm run compile    # One-time compilation
vsce package       # Create VSIX package

Testing

• Open the extension in VS Code's Extension Development Host
• Test with files containing LLM API calls

🚀 Future Enhancements

• Real API Interception: Hook into actual API calls at runtime
• Usage Analytics: Track model usage patterns over time
• Team Insights: Aggregate cost savings across teams
• Auto-Remediation: Automatically optimize models in development
• Multi-IDE Support: Extend beyond VS Code

📊 Performance & Privacy

• ⚡ Fast: Local inference, no network latency
• 🔒 Private: All analysis happens locally
• 📱 Offline: Works without internet after setup
• 🧠 Smart: Fine-tuned Phi-3.5 model for accuracy
• 🌍 Green: Helps reduce AI's carbon footprint

Ready to optimize your AI costs? Install AI-Gauge today! 🚀

Install from VS Code Marketplace